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Simulation of the Urban Jobs–Housing Location Selection and Spatial Relationship Using a Multi-Agent Approach

by 1,2,3, 1,* and 1
1
School of Environment, Beijing Normal University, Beijing 100875, China
2
Research and Development Center for Watershed Environmental Eco-Engineering, Beijing Normal University, Zhuhai 519087, China
3
Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2021, 10(1), 16; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010016
Received: 23 November 2020 / Revised: 28 December 2020 / Accepted: 31 December 2020 / Published: 6 January 2021
The jobs–housing balance concerns the spatial relationship between the number of jobs and housing units within a given geographical area. Due to the separation of jobs and housing, spatial dislocations have occurred in large cities, which have resulted in a significant increase in commuting distance and time. These changes have ultimately led to an increase in pressure on urban traffic, and the formation of tidal traffic. In this study we introduce a multi-agent approach to examine the jobs–housing relationship under the maximum location utility of agents. The jobs/housing ratio measures the balance of the of jobs–housing relationship, as well as comparing and analyzing jobs–housing separation in Beijing by district, county, and street scales. An agent-based model was proposed to simulate spatial location selection behavior of agents by considering environmental and economical influences on residential decisions of individuals. Results show that the jobs–housing relationship imbalance in Beijing has been mainly aggravated due to rapid population growth in the 6th Ring Road. An imbalance in the jobs–housing relationship has arisen due to a mismatch with the number of households available compared to the number of jobs; the surrounding urban areas cannot provide the required volume of housing to accommodate the increase in workers. Six sets of experiments were established to examine resident agents and enterprise agents. Differences in resident agents’ income level had a greater impact on residential location decision-making, and housing price was the primary factor affecting the decision of residents to choose their residential location. The spatial distribution of jobs and housing in Beijing under the maximization of micro-agent location utility was obtained in this study. Results indicated that the imbalance in the jobs¬-housing relationship in central Beijing has improved and, compared with the initial distributions, the number of jobs–housing balance areas in Beijing has increased. View Full-Text
Keywords: jobs–housing relationship; agent-based modeling; location decision-making; Beijing jobs–housing relationship; agent-based modeling; location decision-making; Beijing
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MDPI and ACS Style

Wang, H.; Zeng, W.; Cao, R. Simulation of the Urban Jobs–Housing Location Selection and Spatial Relationship Using a Multi-Agent Approach. ISPRS Int. J. Geo-Inf. 2021, 10, 16. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010016

AMA Style

Wang H, Zeng W, Cao R. Simulation of the Urban Jobs–Housing Location Selection and Spatial Relationship Using a Multi-Agent Approach. ISPRS International Journal of Geo-Information. 2021; 10(1):16. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010016

Chicago/Turabian Style

Wang, Huihui, Weihua Zeng, and Ruoxin Cao. 2021. "Simulation of the Urban Jobs–Housing Location Selection and Spatial Relationship Using a Multi-Agent Approach" ISPRS International Journal of Geo-Information 10, no. 1: 16. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10010016

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